Daniela Wuttig

Serum microRNAs as non-invasive biomarkers for cancer

Human serum and other body fluids are rich resources for the identification of novel biomarkers, which can be measured in routine clinical diagnosis. microRNAs are small non-coding RNA molecules, which have an important function in regulating RNA stability and gene expression. The deregulation of microRNAs has been linked to cancer development and tumor progression. Recently, it has been reported that serum and other body fluids contain sufficiently stable microRNA signatures. Thus, the profiles of circulating microRNAs have been explored in a variety of studies aiming at the identification of novel non-invasive biomarkers.In this review, we discuss recent findings indicating that circulating microRNAs are useful as non-invasive biomarkers for different tumor types. Additionally, we summarize the knowledge about the mechanism of microRNA release and the putative functional roles of circulating microRNAs. Although several challenges remain to be addressed, circulating microRNAs have the potential to be useful for the diagnosis and prognosis of cancer diseases.

A simple strand-specific RNA-Seq library preparation protocol combining the Illumina TruSeq RNA and the dUTP methods

Preserving the original RNA orientation information in RNA-Sequencing (RNA-Seq) experiment is essential to the analysis and understanding of the complexity of mammalian transcriptomes. We describe herein a simple, robust, and time-effective protocol for generating strand-specific RNA-seq libraries suited for the Illumina sequencing platform. We modified the Illumina TruSeq RNA sample preparation by implementing the strand specificity feature using the dUTP method. This protocol uses low amounts of starting material and allows a fast processing within two days. It can be easily implemented and requires only few additional reagents to the original Illumina kit.

microRNA biomarkers in body fluids of prostate cancer patients

The abundance of miRNAs - small non-coding RNAs involved in posttranscriptional regulation of gene expression - in tissues and body fluids of cancer patients hold great promise to identify specific biomarkers, which may be useful for early diagnosis as well as to predict the clinical outcome and treatment response. For the extraction and quantification of miRNAs from cells and tissues, present technologies for transcriptome analyses like microarrays, quantitative real-time PCR or next generation sequencing can be applied. However, the analyses of miRNAs in body fluids like serum or urine is still a challenge with respect to the nucleic acid recovery from very limited sources of biomaterial, normalization strategies and validation using independent technologies. The presence of specific miRNA patterns in body fluids like serum of cancer patients suggests a promising role of these molecules as surrogate markers. However, the majority of miRNA studies were addressed in relatively small patient cohorts limiting the validity and the clinical application of potential miRNA biomarkers or signatures. We reflect the critical steps to translate miRNA biomarker into clinical routine diagnostics and present future aspects for the fast, robust and standardized quantification of miRNAs in body fluids.

CD31, EDNRB and TSPAN7 are promising prognostic markers in clear-cell renal cell carcinoma revealed by genome-wide expression analyses of primary tumors and metastases†

Currently used clinicopathological parameters are insufficient for a reliable prediction of metastatic risk and disease‐free survival (DFS) of patients with clear‐cell renal cell carcinoma (ccRCC). To identify prognostic genes, the expression profiles of primary ccRCC obtained from patients with different DFS — eight synchronously, nine metachronously and seven not metastasized tumors — were determined by genome‐wide expression analyses. Synchronously and metachronously metastasized primary ccRCC differed in the expression of 167 genes. Thirty‐six of these genes were also differentially expressed in synchronously vs. metachronously developed pulmonary metastases analyzed in a previous study. Because of their DFS‐associated deregulation that is concordant in metastases and primary ccRCC, these genes are potentially functionally involved in metastatic tumor growth and are also prognostically useful. A prognostic impact was confirmed for the genes CD31, EDNRB and TSPAN7 at the mRNA level (n = 86), and for TSPAN7 at the protein level (n = 106). Patients with a higher gene expression of EDNRB or TSPAN7, or with TSPAN7‐positive vessels in both cores investigated on tissue microarrays had a significantly longer DFS and tumor‐specific survival (TSS). Patients with a higher CD31 gene expression showed a significantly longer TSS. EDNRB was an independent prognostic marker for the DFS. CD31, EDNRB and TSPAN7 had an independent impact on the TSS. In summary, comparative analysis of primary tumors and metastases is appropriate to identify independent prognostic markers in ccRCC. Gene expression of CD31 and EDNRB, and endothelial TSPAN7 protein level are potentially useful to improve outcome prediction because of their independent prognostic impact.

Graph based fusion of miRNA and mRNA expression data improves clinical outcome prediction in prostate cancer

BackgroundOne of the main goals in cancer studies including high-throughput microRNA (miRNA) and mRNA data is to find and assess prognostic signatures capable of predicting clinical outcome. Both mRNA and miRNA expression changes in cancer diseases are described to reflect clinical characteristics like staging and prognosis. Furthermore, miRNA abundance can directly affect target transcripts and translation in tumor cells. Prediction models are trained to identify either mRNA or miRNA signatures for patient stratification. With the increasing number of microarray studies collecting mRNA and miRNA from the same patient cohort there is a need for statistical methods to integrate or fuse both kinds of data into one prediction model in order to find a combined signature that improves the prediction.ResultsHere, we propose a new method to fuse miRNA and mRNA data into one prediction model. Since miRNAs are known regulators of mRNAs we used the correlations between them as well as the target prediction information to build a bipartite graph representing the relations between miRNAs and mRNAs. This graph was used to guide the feature selection in order to improve the prediction. The method is illustrated on a prostate cancer data set comprising 98 patient samples with miRNA and mRNA expression data. The biochemical relapse was used as clinical endpoint. It could be shown that the bipartite graph in combination with both data sets could improve prediction performance as well as the stability of the feature selection.ConclusionsFusion of mRNA and miRNA expression data into one prediction model improves clinical outcome prediction in terms of prediction error and stable feature selection. The R source code of the proposed method is available in the supplement.

Abstract B42: An integrated view on genetic and epigenetic mechanisms revealed aberrant DNA methylation as an important source for miRNA deregulation in prostate cancer

Prostate cancer (PCa) the most common malignant tumor in males and the third leading cause of cancer-related deaths in Western developed countries. The clinical spectrum of PCa ranges from indolent tumors requiring no therapy to highly aggressive and often metastatic diseases. MicroRNAs (miRNAs) have emerged as important regulators in human tumorigenesis and tumor progression during the last decade. miRNA expression is strongly deregulated in many human cancers including PCa. We investigated the contribution of genetic and epigenetic events to the deregulation of miRNAs in PCa by utilizing the profiling data of 19 Early-Onset Pca (EOPC) from International Cancer Genome Consortium (ICGC) (http://www.icgc.org). For 31% (154/491) of the downregulated miRNAs and for 23% (133/578) of the upregulated miRNAs, DNA hyper- and hypomethylation respectively of a promoter region was observed in at least one of the 13 PCa. Deletions were detected for 26% (126/491) of the downregulated miRNAs in at least one sample. We observed a single translocation event leading to disruption of miR-1244-2 from its putative regulatory region that might contribute to expression decrease. We did not detect any SNV within miRNA precursors. Only one miRNA precursor (miR-4307) was amplified in one patient, but the corresponding mature miRNA was not expressed at all. We demonstrated that, among deletions, methylation of miRNA promoters is one of the major mechanisms leading to miRNA silencing or activation, respectively in PCa. 37 miRNA were downregulated by hypermethylation of regulatory regions and 10 miRNAs were upregulated by hypomethylation in both the ICGC EOPC cohort and the validation dataset on 50 prostate cancer and 48 normal prostate tissues. 82% (9/11) of the miRNAs/miRNA clusters analyzed regulate genes that are involved in PI3K/AKT/PTEN signaling, which represents one of the PCa key pathways being deregulated in more than one third of primary PCa. Note: This abstract was not presented at the conference. Citation Format: Olga Bogatyrova, Daniela Wuttig, Lei Gu, Yassen Assenov, Ruprecht Kuner, Constance Baer, Lars Feuerbach, Clarissa Gerhauser, Dieter Weichenhan, Thorsten Schlomm, Ronald Simon, Guido Sauter, Holger Sultmann. An integrated view on genetic and epigenetic mechanisms revealed aberrant DNA methylation as an important source for miRNA deregulation in prostate cancer. [abstract]. In: Proceedings of the AACR Special Conference on Chromatin and Epigenetics in Cancer; Jun 19-22, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2013;73(13 Suppl):Abstract nr B42.